RSNA and ML: 3 Big Questions

There is no doubt image recognition will be an increasing aspect of our radiology practice. Now what? In addition to the obvious next question on everyone’s mind – how can we use it? here are 3 more.

1. How can we better predict which patients need scanning? Will it be clinical decision support? Will new legislation help or hurt? Can we use the rest of the clinical, social, genomic and family history to better care for patients overall, to included proper imaging?

2. With that, is there a system to support ordering providers, on not just imaging utilization, but working with lab, blood, pharmacy, physical therapy and the many other teammates standing by to help with patient care. Can we decrease variability, improve accuracy and offer more value to the patient and the system?

3. Who is going to carefully follow incidental findings? Does the average radiologist know who is supposed to come in next month for their follow-up scan? Should this duty be taken on by radiology? Can we borrow systems from our colleagues in sales and make a Patient Relationship Management platform like their CRM (Customer)? If ML algorithms are expected to find more than I can, how can we prep for this now?

There will be many RSNA updates over the next week, I’ll be following to see who is thinking about radiology fitting in the bigger picture.

Have fun in Chicago and hope to see you there next year.

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